Abstract
The aim of the study is to develop a decision-making method for choosing a trajectory for processing graphic information in an automated monitoring system for the technical condition of hazardous industrial facilities, taking into account the specifics of the tasks, the conditions for obtaining images and their properties. The study was carried out in several stages, expert assessment of hazardous industrial facilities images; construction of a vector classification feature, including indicators of different nature; selection of the main coordinates for the vector classification feature and construction of a decision-making method for choosing a trajectory for processing graphic information. The paper also presents the obtained solutions for processing graphic information using the example of hazardous industrial facilities at a metallurgical enterprise. The research has been conducted from July 2021 to the present. To conduct the research, system analysis methods are used when performing an expert assessment of images and their classification, generalizing the results of the expert assessment and constructing a decision-making method. The instrumental basis for the software implementation of the obtained trajectories are the Python development environment and the OpenCV library. The constructed trajectories for processing graphic information formed the basis for the multimodular structure of an automated system for monitoring the technical condition of hazardous industrial facilities.
Keywords
image processing, classification features, vector classification feature, image processing trajectory, automated monitoring system, technical condition of objects
1. Narkevich M.Yu. Razvitie metodologii sozdanija sistemy menedzhmenta kachestva metallurgicheskogo predprijatija, jekspluatirujushhego opasnye proizvodstvennye objekty, na osnove prikladnoj cifrovoj platformy. Doct. Diss. [Development of a methodology for creating a quality management system for a metallurgical enterprise operating hazardous production facilities based on an applied digital platform. Doct. Diss.]. Magnitogorsk, 2023. 332 p.
2. Kornienko V.D., Filippov A.Yu., Narkevich M.Yu., Logunova O.S. Method of classification of images of elements of hazardous production facilities. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical systems and complexes], 2024, no. 3(64), pp. 85-92. (In Russian) doi: 10.18503/2311-8318-2024-3(64)-85-92
3. Vlasov Yu.N., Dmitriev G.D. The use of machine vision in the field of computer games for financial gain. Zametki uchenogo [Notes of a Scientist], 2023, no. 2, pp. 255-257. (In Russian)
4. Shcherbakov N.A., Sadov A.A. The possibility of using machine vision to determine the phases of plant growth on the example of tomatoes. Obzor tendentsiy v agropromyshlennom komplekse [Review of trends in the agro-industrial complex: collection of articles of the conference of students, postgraduates and young scientists "Trends in the agro-industrial complex"]. Yekaterinburg, USAU Publ., 2022, pp. 99-100. (In Russian)
5. Afanasyev M.Ya., Fedosov Yu.V., Krylova A.A., Shorokhov S.A. Application of machine vision in the tasks of automatic positioning of tools of modular equipment. Izvestiya vysshikh uchebnykh zavedeniy. Priborostroenie [Journal of Instrument Engineering], 2020, vol. 63, no. 9, pp. 830-839. (In Russian). doi: 10.17586/0021-3454-2020-63-9-830-839
6. Komarov A.S. Evaluation of the quality of digital printing for prompt printing by the method of expert assessments. Izvestiya Tulskogo gosudarstvennogo universiteta. Tekhnicheskie nauki [Izvestiya Tula State University], 2022, no. 12, pp. 419-424. (In Russian). doi: 10.24412/2071-6168-2022-12-419-424
7. Makarov O.A. Application of Expert Assessment in an Integrated Approach to the Assessment of the Industrial Safety of Oil Refineries and Petrochemical Enterprises. Almanakh-2018-1 [Almanac-2018-1]. Volgograd, VSU Publ., 2018, pp. 47-53. (In Russian)
8. Subanov E.E. Analysis of the use of expert assessments in decision-making to assess the degree of risk of collision of vessels. Innovatsionnye podkhody i so-vremennaya nauka [Innovative Approaches and Modern Science], 2011, no. 5-1, pp. 119-123. (In Russian)
9. Garbar E.A. Metod i algoritmy obrabotki informacii v sistemah opticheskogo kontrolja dlja identifikacii defektov poverhnosti listovyh materialov. Kand. Diss. [Method and algorithms for processing information in optical inspection systems for identifying surface defects in sheet materials. Kand. Diss.]. Cherepovets, 2023. 201 p. (In Russian)
10. Bovshik P.A., Berlyakov E.V., Akhmetshin I.N., Logunov S.M. Mobile application for maintenance and repair of equipment of an industrial enterprise: experience in development and implementation. Matematicheskoe i programmnoe obespechenie sistem v promyshlennoy i sotsialnoy sferakh [Mathematical and Software Systems in Industrial and Social Spheres], 2017, vol. 5, no. 1, pp. 30-36. (In Russian)
11. Narkevich M.Yu., Logunova O.S., Arkulis M.B., Sagadatov A.I., Klimov S.S., V Kabanova.V., Nikolaev A.A., Deryabin D.I. Applied Digital Platform for Assessing the Dynamics of the Quality of Hazardous Production Facilities at a Metallurgical Enterprise: Structure and Algorithms. Vestnik Cherepovetskogo gosudarstvennogo universiteta [Cherepovets State University Bulletin], 2022, no. 5(110), pp. 29-48. (In Russian). doi: 10.23859/1994-0637-2022-5-110-3
12. Kornienko V.D., Ezhov G.A., Narkevich M.Yu., Logunova O.S. Classification of initial data for an intelligent system of expert assessment of visually determinable defects and damages. Vestnik Cherepoveckogo gosudarstvennogo universiteta [Cherepovets State University Bulletin], 2022, no. 6(111), pp. 53-64. (In Russian). doi: 10.23859/1994-0637-2022-6-111-4
13. Muratov E.R. Algoritmy predvaritelnoy obrabotki izobrazheniy v sistemakh kombinirovannogo videniya letatelnykh apparatov. Kand. Diss. [Algorithms for Image Preprocessing in Combined Vision Systems of Aircraft. Kand. Diss.]. Ryazan, 2013. 168 p. (In Russian)
Kornienko V.D., Narkevich M.Yu., Filippov A.Yu., Logunova P.S., Torchinskiy V.E. Decision Making Method on the Choice of Image Processing Trajectory Based on Vector Classification Feature. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical Systems and Complexes], 2025, no. 1(66), pp. 58-66. (In Russian). https://doi.org/10.18503/2311-8318-2025-1(66)-58-66